Predictive Nomogram for Midterm to Long-Term Prognosis in Patients with Papillary Renal Cell Carcinoma Based on Data from the Surveillance, Epidemiology, and End Results (SEER) Program.

BACKGROUND This study aimed to develop a predictive nomogram for midterm to long-term prognosis in patients with papillary renal cell carcinoma (RCC) based on data from the US Surveillance, Epidemiology, and End Results (SEER) program. MATERIAL AND METHODS Clinical pathology data and follow-up information were obtained from the SEER database for patients with papillary RCC between 1997-2014. Univariate and multivariate Cox regression models evaluated the independent prognostic factors, and the nomogram was constructed to predict the 3-year, 5-year, and 10-year survival rates. Multiple parameters were estimated to evaluate the predictive values, including the concordance indices (C-indices), calibration plots, area under the receiver operator characteristics (ROC) curve, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). RESULTS The study included 13,926 patients with papillary RCC. Univariate and multivariate Cox regression analysis developed the nomogram that relied on the predictive variables of age, Fuhrman grade, TNM stage, surgery of the primary site, lymphadenectomy, and marital status. The C-indices of the novel model in the validation cohort were more satisfactory than those of the TNM classification. Accurate discrimination and calibration by the nomogram were identified in both cohorts. The NRI and IDI supported prediction improvements, and the DCA supported the nomogram's clinical significance. CONCLUSIONS A nomogram was developed to evaluate the prognosis of papillary RCC and to identify the patients who required specialized treatment. However, external validation of the predictive nomogram is required that also includes patients from other countries.